Energy-saving fuzzy control method and fuzzy control machine in central air conditioner

ABSTRACT

The present invention disclosures a central air-conditioning energy conservation fuzzy control method and fuzzy controller, including: micro-computer, input circuit, output circuit, protective circuit, communication interface circuit, power and micro-computer control program, it is based on the human (expert)&#39;s rich experience and thought to form a fuzzy rule to make inference and judgment, it imitate the expert to resolve the complicated problems in the air-conditioner operation. The precise mathematical model has no need to be established for the controlled central air-conditioner, but only the fuzzy description is needed to realize the controlling. This kind of controlling is more conform the complexity, dynamics and fuzziness of the central air-conditioner, it makes the controlling simple and could realize a best central air-conditioning system operation—safety, comfort and energy conservation.

FIELD OF THE INVENTION

The present invention relates to an intelligent controller of centralair-conditioning energy conservation control system, especially relatesto a central air-conditioning system energy conservation fuzzycontrolling method and device.

BACKGROUND OF THE INVENTION

Currently, along the worldwide energy shortage, the energy conservationcontrolling system design and application are even more emphasized inthe central air-conditioning system design and operation.

In the recent years, with the appearance of high-power electronic parts,it promotes miniaturization and practicality of transducers, in order tocut down the energy waste of central air-conditioning system, thetransducers are used to control the air-conditioning system's water pumpand fan, by the collection of the water system pressure difference andtemperature and make use of the programmable controller (PLC), the waterpump and fan are controlled in way of the PI (proportional, integral)adjustment or the PID (proportional, integral, differential) adjustmentto realize an energy conservation. Owing to the fact that the PLC couldonly realize a simple logic function, it's also called the programmablelogic controller. The PLC control method has a certain energyconservation effect, and the PI controlling or PD controlling has a longhistory with simple principle and easy operation, strong adaptability.But its shortage, however, is as follows:

Firstly, in case the most important project parameter K_(p)(proportional coefficient), T_(I) (integration time constant) and T_(d)(differential time constant) of PI or PID regulator are confirmed, theyare fixed unchangeably if nobody adjusts them, they couldn't be adjustedautomatically with the change of controlled parameters, i.e. once theproject parameters are setup, the same parameters are used for variousoperation conditions. In fact, the central air-conditioning system is akind of time-dependent dynamic system, its operation conditions areaffected by the season, climate, temperature, person flow rate etc, itis changeable momentarily and always stands in the fluctuation. In thisway, the optimal controlling effect couldn't be obtained with the staticparameter control method.

Secondly, the PLC could only realize a simple controlling function ofsingle parameter (temperature or pressure) with somehow better effectsin the single parameter industrial production process controlling, incontrol of, however, the complicated central air-conditioner of moreparameters, non-linearity, time-dependent and strong inner-parametercoupling, the central air-conditioning system would be easily brought tooscillate, and the controlling temperature fluctuates within wide range,and the system couldn't arrive the stabilize state of set value for along time, this not only affects the stability of system, but alsoreduces the comfort of air-conditioning effect.

The central air-conditioning system is a kind of more variable,time-dependent complicated system, its process factors have a badrelationship of non-linearity, large delay and strong coupling. No materthe traditional PID controlling or various algorithms of moderncontrolling theory, a better controlling effect is hard to be realizedwith this kind of system.

For the complicated central air-conditioner with more parameters,non-linearity, time-dependent and strong inner-parameter coupling, theprecise mathematical model couldn't describe it or the model is eithertoo complicated or more rough, the classical mathematics with the mainfeature of accuracy is hard to be successful to this controllingproblem.

A skilled operator or technician, however, may manually control thesystem by his experience, eye, ear and the like with satisfactorycontrolling effects. E.g. the operator may start the refrigerator (orturn on another refrigerator) if the temperature in the building ishigher than set value in summer; otherwise, if the temperature is lowerthan set value, he may stop the refrigerator (or turn off anotherrefrigerator). According to the temperature deviation, if thetemperature is more higher than the set value, more refrigerators are tobe started to lower the temperature fast. The above “higher”, “more”,“fast” etc are all fuzzy concepts. Therefore, the operator's observationand judgment are, in practice, a fuzziness and fuzzy calculationprocess.

CONTENTS OF THE INVENTION

The present invention is purposed to provide a fuzzy control method anddevice for the central air-conditioning system energy conservationcontrolling by making use of the modern fuzzy controlling technology, ifthe man's operational experience, knowledge and technique are induced asa series of rules and stored into the computer, quantifying them by useof the fuzziness collection theory to make the controller to imitate theman's operational strategy and realize a central air-conditionerintelligent controlling to overcome the defect and shortage of currenttechnology; The computer, input circuit, output circuit, protectivecircuit, communication interface circuit, power circuit and its controlsoftware etc compose the fuzzy controller of the centralair-conditioning energy conservation controlling system, and it providesan advanced energy conservation device for the modern centralair-conditioning system.

The purpose of this invention is realized as follows: the fuzzycontroller includes micro computer, input circuit, output circuit,protective circuit, communication interface circuit, power circuit andmicro computer control program, the micro computer realizes a fuzzycontrol algorithm through the control program; the input circuit makesuse of AD7896 single-chip computer to compose the A/D and level convertcircuit; the output circuit makes use of P87LPC768 single-chip computerto compose the D/A and level convert circuit; the protective circuitmakes use of P87LPC764 single-chip computer; the communication interfacecircuit is a full-duplex serial communication interface; the powercircuit includes the voltage stabilized circuit, filter circuit,over-current protection, over-voltage protection.

The fuzzy control method, including the steps of data collection,fuzziness quantum process, fuzziness inference, non-fuzziness process,output etc, the concrete process is as follows:

(1) Data Collection and Model Initialization

In the stage of data collection and model initialization, the fuzzycontroller collects the current flow, current flow-back watertemperature, current water supply temperature of the freezing waterthrough the sensor, and obtains the corresponding signals through theinput circuit, and based on the pre-given freezing water set flow,freezing water flow-back water set temperature and freezing water supplyset temperature, the micro-computer calculates the temperaturedifference deviation and temperature difference deviation change rate interms of the pre-given formulas.

(2) Temperature Difference Deviation Variable Fuzziness

In stage of temperature difference deviation variable fuzziness,according to the temperature difference deviation calculated from thedata collection and model initialization stage, the micro-computer makesuse of the completed program to calculate the temperature differencedeviation affiliation and temperature difference deviation fuzzy value.

(3) Temperature Difference Deviation Change Rate Fuzziness

In stage of temperature difference deviation change rate fuzziness,according to the temperature difference deviation change rate calculatedfrom the data collection and model initialization stage, themicro-computer makes use of the completed program to calculate thetemperature difference deviation change rate fuzzy value and temperaturedifference deviation change rate affiliation.

(4) Fuzziness Inference

The temperature difference deviation fuzzy value calculated from thetemperature difference deviation variable fuzziness stage and thetemperature difference deviation change rate fuzzy value calculated fromthe temperature difference deviation change rate fuzziness stage areused as the input parameters, the micro-computer makes use of thecompleted program to check and calculate the fuzzy control value in thefuzziness rule list.

(5) Fuzziness Value Definition Process

In this stage, using the temperature difference deviation affiliationcalculated from the temperature difference deviation variable fuzzinessstage, the temperature difference deviation change rate fuzzy valuecalculated from the temperature difference deviation change ratefuzziness stage and the fuzzy control value calculated from thefuzziness inference, the micro-computer makes use of the completedprogram and the given formula and checking list to calculate the controlvalue.

(6) Correction Step

In the correction step, using the terminal maximum value and systemdelay of the variable calculated from the various stages above, themicro-computer makes use of the completed program and the givencalculation formula to calculate the correction value.

(7) Output Process

In stage of the output process, according to the control valuecalculated from the fuzziness value definition process stage and thecorrection value calculated from the correction step, the micro-computermakes use of the given formula to program and calculate the frequencyconverter frequency control value, and transfer the control value to thecentral air-conditioning executor through the output circuit to controlthe central air-conditioner operation.

The present invention has the following merits compared with thetraditional technology:

Firstly, it is based on the fuzziness rule of human (expert)'s richexperience and thought to make inference and judgment, and imitate thetechnical expert's deciding process to resolve the complicated problemsresolved by expert. The accurate mathematical model for the controlledobject is not needed, and it only needs a fuzzy description to realizethe controlling. This kind of controlling is more meet the complexity,dynamics and fuzziness of the central air-conditioner, the control isthus simple and the controlling precision is achieved.

Secondly, in the fuzzy controlling, the fuzziness logic languagevariable and its fuzziness relationship are introduced for the fuzzinessinference, the forbidden area could be controlled by computer which isno possible otherwise in the precise model controlling, a precisecontrolling effect is thus obtained on basis of the precise modelcontrolling. Thus the fuzzy controlling has a better energy conservationeffect than the PID controlling.

Thirdly, with the precise control function of fuzzy controlling, thecontrolled frequency converting & speed adjustment of the centralair-conditioning water system realizes the practical operation ofvariable temperature difference, variable pressure difference andvariable flow, the controlling system has a better following and changeability, it could adjust the operation parameters self-suitablyaccording to the controlled dynamic process property identification toget an optimal controlling effect. Obviously, the fuzzy controlling ischangeable, and it is the changeable property that the complicatednon-linearity relationship between the input and output is establishedto effect the intelligent controlling, and it is the complicatednon-linearity that the fuzzy controlling could control the controlledcentral air-conditioning's non-linearity, time-dependent andnon-definiteness etc, and realize the best central air-conditioningsystem operation—safety, comfort and energy conservation.

The present invention may be practiced widely and could be co-operatedwith the new central air-conditioning system, it could also replace thetraditional controlling mode to make technical modification to thepresent central air-conditioning system, and to provide an advancedenergy conservation control device to reduce the energy waste, advancethe usage of energy and lower the central air-conditioning operationcost.

In the present invention, apart from the higher efficiency of energyconservation of central air-conditioning system, the controlledfrequency converting & speed adjustment may realize a smooth starting &stop of the high-powered system pump and fan to reduce the shock andmechanical wearing, the device noise, the device trouble and prolong thedevice usage life. Thus, it has a tremendous economic & society benefit.

BRIEF DESCRIPTION OF THE APPENDED DRAWINGS

FIG. 1 is a block diagram showing an embodiment of a fuzzy controlleraccording to the present invention.

FIG. 2 is a flow chart showing an embodiment of a fuzzy controllingmethod according to the present invention.

DESCRIPTION OF THE EMBODIMENTS

(1) Fuzzy Controller

Refer to FIG. 1, the fuzzy controller according to the present inventionincludes: micro-computer 1, input circuit 2, output circuit 3,protective circuit 4, communication interface circuit 5 and powercircuit 6, the control software is installed in the micro-computer 1.

The micro-computer 1 makes use of the Intel P4 processor with 1.8 GHz,256 MB memory and 40 GB hard disk. The fuzzy control algorithm isrealized by the control software.

The display device supports the pixel of 1024×768 above and the enhancedcolor of 16 bits above.

In the input circuit 2, the AD7896 single-chip computer is used tocompose the A/D and level convert circuit. The fuzzy controller receivesthe signals from the controlled object through the output circuit.

In the output circuit 3, the P87LPC768 single-chip computer is used tocompose the D/A and level convert circuit. The fuzzy controllertransmits the output signal to the executor through the output circuitto control the object to be controlled.

In the protective circuit 4, the P87LPC764 single-chip computer is usedto provide the micro-computer with a “Watchdog” function, in case of thecomputer “deadlock” caused by various interferences, the protectivecircuit would start again automatically, and save the control operationinformation automatically to make the computer recover to its originalworking state.

The communication interface circuit 5 is a 485 full-duplex serialcommunication interface measured up the international standard with thebiggest communication distance of 1200 m, it could transmit theinformation with the controlled equipment in the centralair-conditioning system, transmit the control program command, andreceive the controlled equipment operation information to realize anintellectual controlling.

The power circuit 6 consists of voltage stabilized circuit, filtercircuit, over-current protection and over-voltage protection circuitetc, and provides the micro-computer, input circuit, output circuit,display and protective circuit etc with the power.

(2) Software Part

The core of the fuzzy control software is the fuzzy control rule andfuzziness inference. In the fuzzy control rule, the human (expert)'soperation experience and thought are summed up as a series of conditionsentences, i.e. the control rule, thereby to get a fuzzinessrelationship. Moreover, in the fuzziness inference, the human (expert)'scontrol actions are summed up to educe a fuzziness algorithm rule.

The operational principle of the fuzzy controller is as follows:

The computer receives deviation value of the controlled value and changerate of the deviation value from the input terminal through interruptedsampling, they are all precise values, and the fuzziness set is obtainedafter the fuzziness process, the application of fuzziness inference rulemakes the fuzziness decision by the fuzziness set and fuzzy control ruleto get the corresponding fuzzy control set, and the precise controlvalue is obtained to control the controlled object after thenon-fuzziness (or definition) process.

Then, the computer interrupts to wait for the second data sampling andconducts the second controlling . . . The fuzzy controlling of thecontrolled object is thus realized by repeating the above process.

The fuzzy controlling consists of the following four steps:

(1) obtain the input variable of the fuzzy controller according to thepresent data sampling;

(2) change the input variable exact value to the fuzzy value;

(3) calculate the control value (fuzzy value) by the fuzziness inferenceaccording to the input fuzzy value and fuzzy control rule;

(4) calculate the precise control value by the control value (fuzzyvalue).

As see from the above, the intelligent control based on fuzzinesslogic—fuzzy control, is different from the traditional control theorybased on precise model. The traditional control constitution is:comparison—calculation—control—execution, moreover the intelligent fuzzycontrol constitution is: identification—inference—decision—execution. Itis clear that the fuzzy control is based on the controlled dynamicprocess property identification, and it is the control that based on theknowledge, experience inference and intelligent decision.

Refer to FIG. 2, the fuzzy control rule algorithm of the presentinvention central air-conditioning energy conservation controllingsystem fuzzy controller is as follows:

(1) Data Collection and Model Initialization

In stage of data collection and model initialization, the fuzzycontroller collects the freezing water current flow Q, current flow-backwater temperature T_(back), current water supply temperature T_(supply)through the sensor, and obtains the corresponding signals through theinput circuit, and the micro-computer calculates the temperaturedifference deviation eΔ_(T)(k) and temperature difference deviationchange rate γ (k) by the pre-set formula according to the pre-givenfreezing water set flow Q_(rating), freezing water flow-back water settemperature T_(back rating) and freezing water supply set temperatureT_(suppy rating).

(2) Temperature Difference Variable Fuzziness

In stage of temperature difference deviation variable fuzziness, usingthe temperature difference deviation eΔ_(T)(k) calculated from the datacollection and model initialization stage, the micro-computer makes useof the completed program (checking the list) to calculate thetemperature difference deviation affiliation μ (eΔ_(T)) and thetemperature difference deviation fuzzy value E.

(3) Temperature Difference Deviation Change Rate Fuzziness

In stage of temperature difference deviation change rate fuzziness,using the temperature difference deviation change rate deviation γ (k)calculated from the data collection and model initialization stage, themicro-computer makes use of the completed program and the list tocalculate the temperature difference deviation change rate fuzzy value Γand the temperature difference deviation change rate affiliation μ (γ).

(4) Fuzziness Inference

Make use of the temperature difference deviation fuzzy value Ecalculated from the temperature difference deviation variable fuzzinessstage and the temperature difference deviation change rate fuzzy value Γcalculated from the temperature difference deviation change ratefuzziness stage as the input parameters, the micro-computer makes use ofthe completed program to check and calculate the fuzzy control value Uin the fuzzy rule list.

(5) Fuzziness Value Definition Processor

In this stage, using the temperature difference deviation affiliation μ(eΔ_(T)) calculated from the temperature difference deviation variablefuzziness stage, the temperature difference deviation change rate fuzzyvalue μ (γ) calculated from the temperature difference deviation changerate fuzziness stage, and the fuzzy control value U calculated from thefuzziness inference, the micro-computer makes use of the completedprogram to calculate the control value U(k) by the given formula andlist.

(6) Correction Step

In the correction step, make use of the terminal maximum value a, b andsystem delay d of the variable eΔ_(T)(k), γ (k), eΔ_(T)(k) andeΔ_(T)(k-1) calculated from the various stages above, the micro-computercalculates the correction value q(k) according to the completed programand the given calculation formula.

(7) Output Process

In the output process stage, according to the control value U(k)calculated from the fuzziness value definition process stage, and thecorrection value q(k) calculated from the correction step, themicro-computer calculates the frequency converter's frequency controlvalue f(k) in terms of the given formula based computer program, and thecontrol value is transmitted to the central air-conditioning executor tocontrol the central air-conditioning operation through the outputcircuit.

1. A central air-conditioning energy conservation fuzzy controller,including: micro-computer (1), input circuit (2), output circuit (3),protective circuit (4), communication interface circuit (5), powercircuit (6) and micro-computer control program, characterized in that:the micro-computer (1) realizes a fuzzy control algorithm through thecontrol program; the input circuit (2) makes use of AD7896 single-chipcomputer to compose the A/D and level convert circuit; the outputcircuit (3) makes use of P87LPC768 single-chip computer to compose theD/A and level convert circuit; the protective circuit (4) makes use ofP87LPC764 single-chip computer; the communication interface circuit (5)is a full-duplex serial communication interface; the power circuit (6)includes the voltage stabilized circuit, filter circuit, over-currentprotection, over-voltage protection.
 2. A central air-conditioningenergy conservation fuzzy control method, characterized in that:including the steps of data collection, fuzziness quantum process,fuzziness inference, non-fuzziness process, output etc, the concreteprocess is as follows: (1) Data collection and model initialization Inthe stage of data collection and model initialization, the fuzzycontroller collects the current flow, current flow-back watertemperature, current water supply temperature of the freezing waterthrough the sensor, and obtains the corresponding signals through theinput circuit, and based on the pre-given freezing water set flow,freezing water flow-back water set temperature and freezing water supplyset temperature, the micro-computer calculates the temperaturedifference deviation and temperature difference deviation change rate interms of the pre-given formulas. (2) Temperature difference deviationvariable fuzziness In stage of temperature difference deviation variablefuzziness, according to the temperature difference deviation calculatedfrom the data collection and model initialization stage, themicro-computer makes use of the completed program to calculate thetemperature difference deviation affiliation and temperature differencedeviation fuzzy value. (3) Temperature difference deviation change ratefuzziness In stage of temperature difference deviation change ratefuzziness, according to the temperature difference deviation change ratecalculated from the data collection and model initialization stage, themicro-computer makes use of the completed program to calculate thetemperature difference deviation change rate fuzzy value and temperaturedifference deviation change rate affiliation. (4) Fuzziness inferenceThe temperature difference deviation fuzzy value calculated from thetemperature difference deviation variable fuzziness stage and thetemperature difference deviation change rate fuzzy value calculated fromthe temperature difference deviation change rate fuzziness stage areused as the input parameters, the micro-computer makes use of thecompleted program to check and calculate the fuzzy control value in thefuzziness rule list. (5) Fuzziness value definition process In thisstage, using the temperature difference deviation affiliation calculatedfrom the temperature difference deviation variable fuzziness stage, thetemperature difference deviation change rate fuzzy value calculated fromthe temperature difference deviation change rate fuzziness stage and thefuzzy control value calculated from the fuzziness inference, themicro-computer makes use of the completed program and the given formulaand checking list to calculate the control value. (6) Correction step Inthe correction step, using the terminal maximum value and system delayof the variable calculated from the various stages above, themicro-computer makes use of the completed program and the givencalculation formula to calculate the correction value. (7) Outputprocess In stage of the output process, according to the control valuecalculated from the fuzziness value definition process stage and thecorrection value calculated from the correction step, the micro-computermakes use of the given formula to program and calculate the frequencyconverter frequency control value, and transfer the control value to thecentral air-conditioning executor through the output circuit to controlthe central air-conditioner operation.
 3. The central air-conditioningenergy conservation fuzzy control method according to claim 2,characterized in that: the calculation formula of the temperaturedifference deviation and temperature difference deviation change rate inthe said data collection and model initialization step is:


4. The central air-conditioning energy conservation fuzzy control methodaccording to claim 2, characterized in that: the calculation formula ofthe temperature difference deviation affiliation and temperaturedifference deviation fuzzy value in the temperature difference deviationvariable fuzziness step is:


5. The central air-conditioning energy conservation fuzzy control methodaccording to claim 2, characterized in that: the calculation formula ofthe temperature difference deviation change rate fuzzy value andtemperature difference deviation change rate affiliation in thetemperature difference deviation change rate fuzziness step is:


6. The central air-conditioning energy conservation fuzzy control methodaccording to claim 2, characterized in that: the fuzziness rule list offuzzy control value calculated in the fuzziness inference step is:


7. The central air-conditioning energy conservation fuzzy control methodaccording to claim 2, characterized in that: the calculation formula ofthe control value in the fuzziness value definition process step is:


8. The central air-conditioning energy conservation fuzzy control methodaccording to claim 2, characterized in that: the calculation formula ofthe correction value in the correction step is:


9. The central air-conditioning energy conservation fuzzy control methodaccording to claim 2, characterized in that: the calculation formula ofthe frequency converter frequency control value in the output processstep is: